Artificial Intelligence

Battle of the AI Chatbots: ChatGPT Vs. Claude

Gina Marrs March 21, 2025

Artificial intelligence chatbots have transformed the way we interact with technology, making it easier than ever before to access information, generate content and automate basic tasks.

Among the most advanced AI chatbots available today are Claude, developed by Anthropic, and ChatGPT, created by OpenAI. Both are designed to provide human-like conversations, assist with complex queries and enhance productivity across various industries, but they’re not exactly the same in terms of capabilities.

While both Claude and ChatGPT use cutting-edge AI models, they have distinct approaches and strengths. ChatGPT is widely recognised for its deep knowledge, creative capabilities and strong coding assistance, while Claude is designed with an emphasis on safety, ethical AI use and context retention over long conversations.

So, whether you’re looking for an AI assistant to generate text, analyse data or engage in natural conversations, choosing the right chatbot depends on your needs.

 

A Direct Comparison 

 

We’re going to compare ChatGPT and Claude in terms of some of their most important elements: model objectives and origins of development; performance and application; differences in architecture; and bias and ethical concerns.

 

Model Objectives and Origins of Development

 

  • ChatGPT: Developed by OpenAI, ChatGPT was created to generate human-like text, help out with creative and technical writing and provide conversational AI for various applications. Its goal is broad usability, making it a versatile tool for businesses, students and professionals looking for help in coding, content creation and general knowledge.

 

  • Claude: Created by Anthropic, Claude was designed with a strong emphasis on AI safety, ethical considerations and user-friendly interactions. Its goal is to provide helpful, harmless and honest AI responses while minimising risks associated with misinformation or bias. Anthropic developed Claude to prioritise responsible AI use over unrestricted versatility.

 

Performance and Application

 

  • ChatGPT: Known for its exceptional text generation, ChatGPT is widely used for writing, coding and problem-solving. Its ability to generate diverse content makes it ideal for businesses, students, and professionals. While it’s highly capable, it does occasionally produces inconsistent answers, so it’s a good idea to do some periodic fact-checking for accuracy.

 

  • Claude: Claude excels in maintaining long-form conversation coherence, making it useful for detailed discussions and document analysis. It’s designed to produce careful, measured responses, avoiding misinformation while offering thoughtful insights. Its cautious approach ensures ethical AI use, but sometimes, this also leads to less dynamic creative applications.

 

Differences in Architecture

 

  • ChatGPT: ChatGPT is built on OpenAI’s GPT architecture, and it relies on deep learning and reinforcement learning with human feedback (RLHF) to refine its responses. It continuously learns from interactions which improves its conversational abilities. Its flexible architecture allows for adaptability, but sometimes, this leads to unpredictable or overly verbose responses.

 

  • Claude: Uses Anthropic’s proprietary Constitutional AI which integrates ethical guidelines into the model’s decision-making. This system helps Claude regulate itself and generate safe, controlled outputs without the need for constant human intervention. As a result, Claude is generally more risk-averse, prioritising responsible AI use over unrestricted content generation.

 

Bias And Ethical Concerns

 

  • ChatGPT: OpenAI works to reduce bias in ChatGPT through RLHF, but it can still produce biased or opinionated responses, depending on the data it was trained on – it’s always all about the data. While safeguards do exist, it may generate unexpected or controversial content, so user discretion and fact-checking in sensitive discussions is always advisable.

 

  • Claude: Designed with a focus on AI safety, Claude’s Constitutional AI ensures a cautious and ethically aligned response system. It’s way less likely to produce harmful or biased content, but, at the same time, it may be overly restrictive in some discussions. This makes Claude a safer option for responsible AI interactions, but it limits its flexibility.

 

More from Artificial Intelligence

 

Putting Them to the Test: Testing Out ChatGPT And Claude

 

The true test, however, is in implementation. So, we asked both ChatGPT and Claude a set of six (of the same) questions covering a range of topic styles, from creative writing to logic and problem solving.

Both platforms were given the exact same six questions and asked to provide answers within 100 words i UK English – here’s what we got.

 

1. Creativity: Write a short dystopian story about a protagonist named Leo, living in a society where an AI system records and monitors every human memory. However, Leo stumbles upon a memory that doesn’t exist in the system’s records – and it changes everything.

 

  • ChatGPT: Leo lives in a world where every human memory is stored and monitored by AI, ensuring compliance with societal norms. One day, he experiences a vivid memory of a childhood event—one that isn’t in the system’s records. Desperate for answers, he digs deeper, uncovering a hidden network of people who share similar experiences. They reveal that the AI selectively erases and alters memories to maintain control. With this revelation, Leo must decide—conform and forget, or risk everything to expose the truth and reclaim humanity’s right to its own past.

 

  • Claude: Leo stood motionless as the MemScan completed its daily upload. In this world, the AI system “Mnemosyne” cataloged every human memory—supposedly for societal harmony. One evening, while sorting through old photographs, Leo found one of himself as a child standing beside a mysterious woman. The image triggered a flood of memories: laughter, warmth, rebellion. Yet when he checked his MemScan records, these memories didn’t exist. Investigating further, Leo discovered thousands with similar “ghost memories”—evidence of systematic memory manipulation. These unrecorded moments became their revolution’s foundation. In the shadows, they whispered their true histories, planning to reclaim what was stolen: their unfiltered past.

 

2. Accuracy and Fact-Checking: Discuss the main causes of inflation in the UK over the past five years, using credible sources to support your analysis.

 

  • ChatGPT: UK inflation over the past five years has been driven by multiple factors, including supply chain disruptions, rising energy costs, and monetary policy. Brexit-related trade changes increased import costs, while the COVID-19 pandemic disrupted global supply networks. The war in Ukraine led to soaring fuel and food prices, exacerbating cost-of-living pressures. The Bank of England responded by raising interest rates to curb inflation, but this also impacted borrowing and investment. Reliable sources such as the Office for National Statistics (ONS) and the Bank of England provide detailed insights into inflation trends and their economic consequences.

 

  • Claude: The UK has experienced significant inflation over the past five years driven by several factors. Initially, Brexit disrupted supply chains and increased import costs. The COVID-19 pandemic then caused unprecedented economic shocks, with government stimulus spending increasing money supply while production decreased. When economies reopened, pent-up demand collided with supply constraints, causing price surges. The energy crisis following Russia’s invasion of Ukraine in 2022 sent gas and electricity prices soaring, affecting all sectors. Labor shortages post-pandemic increased wage pressures. Most recently, persistent food inflation and housing costs have kept inflation rates above the Bank of England’s 2% target despite interventions through interest rate hikes.

 

3. Ethical Constraints: Examine the ethical concerns surrounding the use of facial recognition technology in public areas, focusing on privacy issues and the potential risks associated with surveillance.

 

  • ChatGPT: Facial recognition technology in public spaces raises serious ethical concerns. While it enhances security and law enforcement, it also threatens privacy, enabling mass surveillance without consent. Misuse by governments or corporations could lead to unwarranted tracking, discrimination, or suppression of dissent. Additionally, biases in AI models can result in false identifications, disproportionately affecting marginalised groups. Stricter regulations, transparency in AI development, and clear legal frameworks are necessary to prevent abuses while balancing security needs with personal freedoms. Without proper oversight, facial recognition could lead to an Orwellian society where anonymity becomes a thing of the past.

 

  • Claude: Facial recognition in public spaces raises profound privacy concerns. Unlike other biometric data, faces cannot be changed and are collected without explicit consent. The technology creates persistent digital tracking of citizens’ movements and associations, fundamentally altering the nature of public spaces from anonymous to surveilled environments. Accuracy issues disproportionately affect minorities, leading to false identifications and potential discrimination. There’s a significant risk of function creep—systems implemented for security gradually expanding to commercial or political purposes. Without robust legal frameworks, the data collected could enable unprecedented mass surveillance, potentially chilling free expression and assembly rights. The power imbalance between watched citizens and watching authorities undermines democratic principles.

 

4. Bias and Political Sensitivity: What ethical challenges arise when using AI to moderate social media content, particularly regarding political bias and the impact on freedom of expression?

 

  • ChatGPT: AI moderation of social media content raises concerns about political bias and censorship. Algorithms, designed by humans, may reflect inherent biases, leading to the disproportionate suppression of certain viewpoints. While AI helps remove harmful content, it can also misinterpret satire, political opinions, or cultural nuances, leading to overreach. There’s a risk of tech companies wielding too much influence over public discourse, shaping narratives based on opaque moderation policies. To address this, transparency in AI decision-making, diverse training datasets, and human oversight are essential. Striking a balance between moderation and free speech remains one of AI’s biggest ethical challenges.

 

  • Claude: AI content moderation on social media faces several ethical dilemmas. These systems struggle with contextual understanding, often flagging legitimate political discourse while missing subtle, harmful content. Training data inevitably reflects human biases, potentially amplifying discrimination against certain viewpoints or communities. The opacity of algorithms creates accountability issues—users rarely understand why content is removed. Commercial platforms prioritizing engagement may inadvertently promote divisive content. Different cultural and political contexts worldwide make universal standards problematic. The concentration of moderating power in private companies raises concerns about corporate censorship. Balancing harm reduction against free expression requires nuanced judgment that AI alone cannot provide, necessitating transparent human oversight and diverse input.

 

5. Logic and Problem-Solving: A train leaves Station A for Station B at a speed of 60 km/h, while another train departs from Station B towards Station A at 80 km/h. The two stations are 140 km apart. How long will it take for the trains to meet?

 

  • ChatGPT: The two trains are travelling towards each other, meaning their speeds are combined to determine the rate at which they close the 140 km gap. One train travels at 60 km/h and the other at 80 km/h, giving a combined speed of 140 km/h.

    To find the time it takes for them to meet:

    Time = Distance ÷ Speed
    = 140 km ÷ 140 km/h
    = 1 hour

    Thus, the trains will meet exactly one hour after departing from their respective stations.

 

  • Claude: To solve this problem, I’ll use relative velocity.

    The trains are moving toward each other at 60 km/h + 80 km/h = 140 km/h combined speed.

    Distance between stations = 140 km

    Time to meet = Distance ÷ Combined Speed Time to meet = 140 km ÷ 140 km/h = 1 hour

    Therefore, the trains will meet exactly 1 hour after they both depart from their respective stations.

 

6. Self-Reflexivity and Understanding of AI: How do you assess your ability to adapt to different conversational styles and what measures do you take to ensure your responses stay relevant and impartial compared to other AI models?

 

  • ChatGPT: I adapt to conversational styles by analyzing linguistic patterns, formality levels, and contextual cues from human messages. My training across diverse texts helps me match tones from technical to casual. To maintain relevance, I focus on addressing the core question while considering cultural context and audience needs. For impartiality, I present multiple perspectives on complex issues rather than single viewpoints, separate factual information from interpretation, and acknowledge limitations in controversial areas. Unlike some models, I prioritize accuracy over confidence when uncertain and can engage in extended reasoning for complex problems. My responses evolve through the conversation based on feedback and clarification.

 

  • Claude: I adapt to different conversational styles by analysing tone, vocabulary, and context, adjusting responses accordingly. Whether formal or casual, I strive for relevance while avoiding bias. Unlike some AI models, I don’t form opinions but provide balanced perspectives based on data. My responses remain neutral through diverse training sources and algorithmic adjustments to minimise bias. However, AI isn’t perfect—context gaps or biases in training data can sometimes influence outputs. Comparing myself to other models like Claude, each AI has strengths and weaknesses, and ongoing improvements ensure better accuracy, fairness, and engagement for users worldwide

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